The proposed research focuses on theoretical studies of two problems of fundamental significance to the elucidation of the relationship between the structure and function of biopolymers. These are : 1) the occurrence and biochemical ramifications of alternative modes of hydrophobic hydration, and 2) the modelling of chemical bond rearrangements associated with enzymatic activity, with emphasis on proton transfer. Hydrophobic interactions are recognized as a principal contributor to the conformational stability of globular proteins and a key driving force for association phenomena involving biomolecules, and this area will be the primary initial focus. Specifically, we will probe the potentially critical role played by hydration of extended or concave hydrophobic surface regions of folded polypeptides in the context of structural design and its role in stability, solubility and nonbonded association with other species, including enzymatic substrates. The quantitative significance will be examined via free energy perturbation calculations. The studies will be carried out by computer simulation of a selected set of polypeptide systems and specific model systems in water. Proton transfer is a ubiquitous biochemical process present in metabolic catalysis and in active transport across cell membranes. In this second area of investigation, we will focus on the development of our recent novel, semiempirical, scheme for the description of covalent interactions in this biophysical context. The format of the model describes interactions through separate local bonding and nonbonding interactions and is capable of representing each in compact and computationally rapid form. Successful development of the model will enable the inclusion of medium dynamics and nuclear tunnelling effects into biophysical studies with retention of computational efficiency. Initial applications will include those to water and to lysozyme. Pursuit of these projects will enhance both our understanding of the origins of biopolymer behavior and our ability to quantitatively evaluate this behavior computationally.